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Finite-time and fixed-time anti-synchronization of neural networks with time-varying delays

机译:具有时变时滞的神经网络的有限时间和固定时间反同步

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In this paper, the finite-time and fixed-time anti-synchronization of master-slave dynamical systems with time-varying delays are investigated. The feedback controller is designed only depending on the system state at present time t, but independent of the delayed states, which would be much easier to be verified and realized in practice. Rigorous analysis is developed in two cases with respect to the different ranges of initial state of error systems. Then the absolute value of each error state component can be considered as that, flowing from the initial value to 1 first, then from 1 to 0, and the time it needs in this whole process is finite. As special cases, several neural network models with unbounded time delays are addressed to illustrate the effectiveness and efficiency of our obtained results. (C) 2018 Elsevier B.V. All rights reserved.
机译:研究具有时变时滞的主从动力系统的时滞和定时反同步问题。反馈控制器的设计仅取决于当前时间t的系统状态,而与延迟状态无关,这在实践中将更易于验证和实现。针对错误系统的初始状态的不同范围,在两种情况下进行了严格的分析。然后,可以将每个错误状态分量的绝对值视为从初始值到1,然后从1到0的绝对值,并且在整个过程中所需的时间是有限的。作为特殊情况,提出了具有无限时延的几种神经网络模型,以说明我们获得的结果的有效性和效率。 (C)2018 Elsevier B.V.保留所有权利。

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